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Field
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and across multiple scientific areas, CALS can address challenges and opportunities of the greatest relevance, here in New York, across the nation, and around the world. Starting Date: As soon as
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functional data ”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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. Proficiency with scripting or programmatic languages, such as Python, Igor, and labview. Excellent written and oral communication skills. Motivated self-starter with the ability to work independently and to
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in software development skills in programming languages such as R and Python. Knowledge, Skills and Abilities Skill in managing one’s own time and the time of others. Ability to analyze, organize and
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Science, Statistics, Mathematics, Computer Science, or a closely related field. Demonstrated expertise working with multivariate time-series and spatiotemporal datasets. Advanced proficiency in Python
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., cracking systems, storage, gas power cycle, gas turbine) Familiarity with Systems Engineering approach Experience with: ASPEN plus ASPEN Hysys Python or relevant programing language Transient simulations
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by multiple orders-of-magnitude. This is an exciting opportunity to be at the forefront of using advanced computational methods and systems, including machine learning, to develop data and computing
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Expertise and hands-on experience using LLMs, Machine Learning, Deep Learning frameworks, Natural Language Processing, etc. Proficient programming skills in Python and R and working knowledge in SQL Strong
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: Employing satellite observation and machine leaning to improve model representation of ice sheet surface melt”. The candidate will work under the direction of Prof Nowicki and in collaboration with multiple
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candidate will work under the direction of Prof Nowicki (UB) and Prof Kopp (Rutgers) and in collaboration with multiple UB faculty and students as well as our external collaborators located at NASA Goddard